AI will change absolutely everything, but IT more than most. That transformation, though, isn’t something that leaders can take for granted; they have to be proactive and make it happen. Intel, for its part, is making representation happen with a commitment to investing in women-owned businesses, and Microsoft is helping with the transition from legacy hardware. It’s all worth it, too. With that transformation comes more data, more insights, and more value.
Artificial intelligence is going to accelerate, transform, and generally smart-ify every aspect of business and industry. However, some areas are going to feel the effects of AI a bit more than others, and IT is poised to be affected the most. With AI, IT will be a source of data-fueled insight and an engine of internal innovation, and that’s just the tip of the tip of the transformative iceberg.
The ancient Greeks had a whole bunch of muses. They had one for tragedy, one for love poetry, and another for astronomy. They also had muses for history and epic poetry but, unfortunately, no muses for technology. That means no divine daughter of Zeus can help IT decision-makers with digital transformation. Instead, leaders need to take action themselves to make it happen.
Intel is committed not just to recognizing women and minorities, but to employing and working with them. We set internal hiring goals to bring women and underrepresented minorities into our ranks and met them. We’re also committed to working with women-owned businesses, and hope to spend $200 million annually with them by 2020.
Imagine if legacy technology was everywhere. Your rideshare could be a horse-drawn taxi. Airlines would still offer Zeppelin rides. Steam trains would be a regular sight. As charmingly old-timey as this might seem, it wouldn’t take long for you to miss airplanes. Plenty of businesses still use the IT-equivalent of Zeppelins, though, and need to move into the future (or, at the very least, the present).
Mining, generally, is not a quest to find rocks. Rocks are really easy to find. Mining is all about finding the good stuff in the rocks, and to do that miners need tools like pickaxes and gigantic drill-shaped boring machines. Data, likewise, is sort of like rocks, and analytics are kind of like the boring machines that can yield gems of insight, veins of actionable information, and mother-lodes of value.